Control of a Conveyor Based on a Neural Network

Oleh Pihnastyi and Georgii Kozhevnikov

MPRA Paper from University Library of Munich, Germany

Abstract: The present study is devoted to the design of the main flow parameters of a conveyor control system with a large number of sections. For the design of the control system, a neural network is used. The architecture of the neural network is justified and the rules for the formation of nodes for the input and output layers are defined. The main parameters of the model are identified and analyzed. The data set for training the neural network is formed using the analytical model of the transport system. The criterion for the quality of the transport system is written. For the given criterion for the quality of the transport system, the Pontryagin function is defined and the adjoint system of equations is given. It allows calculating optimal control of the transport system. For calculation is used additional model of the transport system with output nodes which are controls. A graphical representation of the results of the study is given

Keywords: PDE-model production; PiKh-model; distributed system; optimal control (search for similar items in EconPapers)
JEL-codes: C02 C15 C25 C44 D24 L23 Q21 (search for similar items in EconPapers)
Date: 2020-10-09, Revised 2021-10-09
New Economics Papers: this item is included in nep-cmp
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Published in International Conference on Problems of Infocommunications. Science and Technology (PIC S&T) (2020): pp. 295-300

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:111950

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